Managing body composition

ABSTRACT

Among other things, at least two different independent providers of body composition management services are enabled to have online access through respective graphical user interfaces to body composition information and plans that are associated with respective clients of the providers and that are stored on the server. The graphical user interfaces are different for different independent providers. At least some of the information and plans associated with the clients of the different independent providers are stored in a common format in a common database maintained by the server.

CLAIM OF PRIORITY

This application is a divisional and claims priority under 35 U.S.C.§120 to U.S. patent application Ser. No. 11/948,702, filed Nov. 30,2007, now U.S. Pat. No. 7,788,042, the entire contents of which arehereby incorporated by reference.

This description relates to managing body composition.

Body composition generally refers to how much fat, bone, internal organtissue, and muscle make up a person's body. The lean body mass (LBM)(bone, internal organ tissue, and muscle) and fat body mass (FBM) in aperson's body depend significantly on three major factors: geneticpredisposition, what food and how much of it the person eats, and theextent to which the person exercises or is generally active.

Body composition may affect a person's health and appearance. Strengthand stamina, for example, depend on a foundation of well-developedand/or conditioned lean body mass. A person who is fat (that is, who hasa high percentage of fat body mass) is thought to be at higher risk ofdisease and systemic health problems. On the other hand, it is essentialfor good health to have a minimum percentage of fat body mass.

The overall base metabolic rate (BMR) of a person (which affects howeasily the person can “burn” the calories that he consumes) depends uponthe total weight of the person's lean body mass. Lean body mass has ahigher metabolic rate than fat body mass for a given body weight. Givena certain amount of lean body mass in a person's body, a person withmore fat body mass may tend to consume relatively more calories than hisbody is able to burn than would a person having the same lean body massand less fat body mass. The excess calories consumed by the fatterperson are stored as additional fat, which can degrade the person'shealth.

People in certain cultures, and those who understand and monitor howtheir bodies work, pay close attention to their body compositions andfollow casual or strict dietary and exercise training programs aimed atreaching and maintaining (e.g., managing) a desirable body composition.Sometimes people rely on others, including trainers, dieticians, andhealth practitioners to help them manage their body compositions.

Effective management of body composition over a period of time dependson having good metrics for aspects of body composition. The metricsshould be reasonably easy to measure or calculate and should representaspects of body composition that are important to the strength, stamina,appearance, and health goals of the individual who uses them.

A classic metric is the relationship between a person's weight andheight compared to other people of the same gender. Although easy tomeasure, the person's weight alone gives essentially no informationabout the proportions of lean body mass and fat body mass that make upthe body. Height is also easy to measure, and the weight and height of aperson, when considered together with percentage of body fat, may giveclues about the relationship of lean body mass to fat body mass.

Another metric, body mass index (BMI) relates weight to height by asimple mathematical formula that yields a value on a scale that is usedto classify the general fatness or thinness of a person within broadstatistical norms in the general population, which change significantlyover long periods of time. Ranges of BMI values are sometimes associatedwith corresponding degrees of healthiness.

Another commonly used metric is the percentage of fat mass in a person'sbody. While historically difficult to measure accurately, there are nowmany techniques for determining fat mass percentage accurately and thereare medically accepted standards that associate ranges of the value withdegrees of physical training and health.

Trainers, dieticians, and others (for example, health practitioners) whohelp people to follow programs to manage their body compositionstypically perform measurements of one or more of the metrics at thebeginning of the program, set targets for the metrics to be achieved,and make regular measurements during the course of the program to gaugeprogress in reaching the targets. How accurately and regularly themeasurements are taken, and how effectively information about how theyrelate to the person's health, strength, and stamina are described,displayed, and understood, have much to do with how effectively theprogram progresses toward the targets. In some cases, computer programsand online systems can be used to record and track metrics againstgoals.

SUMMARY

In general, in an aspect, at least two different independent providersof body composition management services are enabled to have onlineaccess through respective graphical user interfaces to body compositioninformation and plans that are associated with respective clients of theproviders and that are stored on the server. The graphical userinterfaces are different for different independent providers. At leastsome of the information and plans associated with the clients of thedifferent independent providers are stored in a common format in acommon database maintained by the server.

Implementations may include one or more of the following features. Theproviders include trainers and entities that employ trainers. Thegraphical user interfaces include common elements and private labelelements.

In general, in an aspect, a value of maximum fat mass is determined thatrepresents an amount of fat mass that an individual should not exceedfor good health. The value of maximum fat mass is determined as afunction of height and gender based on a body of statistical data acrossa population. A value of minimum lean mass is determined that representsan amount of lean mass that the individual should not fall below forgood health, the value of minimum lean mass being determined as afunction of height and gender based on a body of statistical data acrossa population. The individual or a trainer of the individual is enabledto manage body composition of the individual based on the determinedvalues of the maximum fat mass and the minimum lean mass.

Implementations may include one or more of the following features. Theenabling includes displaying information associated with the determinedmaximum fat mass and minimum lean mass and measured fat mass and leanmass of the individual to the individual or trainer. A lean mass ratioand a fat mass ratio are determined from respectively the minimum leanmass value and a measured lean mass, and the maximum fat mass value anda measured fat mass. The lean mass ratio and the fat mass ratio areprovided to the individual or the trainer for use in connection withmanagement of body composition of the individual.

In general, in an aspect, demographic, health status, and lean mass, fatmass, and other physical data about individuals are received,statistical analyses of the received data are performed to establishdemographic lean mass and fat mass values, and the values are madeavailable to individuals and parties who provide services to individualsin connection with managing body composition, without disclosing theidentities or private information of any of the individuals about whomthe data was received.

Implementations may include the following feature. The physical data isreceived from the individuals or parties who provide services to theindividuals.

In general, in an aspect, a target body composition management value isderived for a person from the person's height, weight, body masscomposition, and statistical physical information about a comparablepopulation of individuals. The target body composition management valueis provided for use in managing the person's body composition.

Implementations may include one or more of the following features. Thetarget body composition management value includes a body mass index(BMI) value. The target body composition management value includes aversion of a conventional BMI value that is adjusted based on bodycomposition data. The conventional BMI value is adjusted upwardly inproportion to a value based on lean body mass and downwardly inproportion to a value based on fat body mass. Information about thetarget body composition management value is displayed to the client or atrainer. The information includes the conventional BMI value and anadjusted BMI value. The information includes graphical elementsillustrating an effect of fat body mass or lean body mass or both on anappropriate BMI value.

In general, in an aspect, a target value associated with a targeted fatmass and lean mass body composition of a person to be achieved by afuture date is generated. A slope is displayed that begins at a startingpoint associated with a starting date and ends at an ending pointassociated with the future date, the starting point representing astarting value and is based on measurements on the starting date. Atrajectory is displayed that traverses mid-points having values that arebased on measurements on dates between the starting date and the endingdate.

Implementations may include one or more of the following features. Thetarget value is associated with weight. The target value is associatedwith a component of body mass. The component of body mass includes fatmass or lean mass. The target value is associated with a ratio for acomponent of body mass. The ratio includes fat mass ratio or lean massratio. The slope includes a straight line. The slope and the trajectoryare displayed at the same time. The slope and the trajectory areassociated with a goal session for the person.

These and other aspects and features, and combinations of them may beexpressed as methods, systems, apparatus, combinations, programproducts, and means for performing functions, and in other ways.

Other advantages and features will become apparent from the followingdescription and from the claims.

DESCRIPTION

FIG. 1 is a block diagram.

FIGS. 2 through 7 are portions of a database schema.

FIGS. 8 through 20 are line drawing representations of screen shots.

FIG. 21 is a table.

FIG. 22 is a graph.

FIGS. 23A, 23B, and 23C are a report.

FIGS. 24, 25, 26, and 27 are graphs.

FIG. 28 is a BMI diagram.

For good health, strength, and stamina, a person's body should have atleast a certain minimum lean mass (MLM) and a certain maximum fat mass(MFM). Having more lean mass than the minimum is generally good as ishaving no more than the maximum fat mass. The desirable minimum leanmass and maximum fat mass can be determined for a person and set asgoals for a body composition management program. In order to track aperson's performance against those goals, the actual lean body mass andthe actual fat body mass can be measured, by various methods, at thebeginning of the program and regularly during the program. By storingand making available information about progress with respect to theminimum lean mass and maximum fat mass and other metrics, the person'sdietary and training efforts can be sharply focused on the metrics thatmatter, and success of the program is more likely.

As shown in FIG. 1, in some implementations of the system describedhere, a body composition management system 10 provides online bodycomposition management services and information to (and receives,accumulates, and analyzes information received from) one or moretrainers 12, 14, 16 . . . 18, one or more partners 22 . . . 24, and oneor more individual clients 28 . . . 32 to aid them in effectivelymanaging the body compositions of the clients. In these examples,managing body composition can include, for example, acceptingregistrations by the partners, the trainers, and the clients, receivingand storing data and measurements about each of the clients, one or moretimes, receiving and storing information about body composition goals ofthe clients, storing the measured values and goal information over time,and reporting the information to the clients, the trainers, and thepartners.

The body composition management services may be provided from one ormore servers or other computers and from one or more other stationary orportable electronic devices 34, 36, 38 . . . 40 that are located with aclient, with a trainer, with a partner, or at a central location 48. Thebody composition management services may be provided using anapplication program 50, 52 that may be running in association with acentral web server 55 that delivers the services through a network 57such as the Internet, or as a standalone application running in alocation associated with a partner, a trainer, or a client. In someimplementations, the services can be provided by a cooperative operationof applications running at a server and a local facility.

All or portions of the information required to operate the system arestored, maintained, and accessed in a database 54, 56 . . . 36, that canbe located only at the server or only at local facilities or can bedistributed at a number of different locations.

The clients who are served by the system 10 are individuals who seek tomanage their body compositions for good health, good appearance,stamina, and/or strength. The number of clients served by the systemcould range from only a few to hundreds, thousands, or even millions.They could be located in cities or rural areas anywhere in the world.They may or may not be associated with trainers and partners.

We use the term trainer to refer to any individual who is an exercise orstrength trainer, a dietician, a health professional, or otherindividual who helps clients, directly or indirectly, to manage one ormore aspects of their body compositions and to reach goals associatedwith body composition management. The number of trainers involved in thesystem could range from only a few to dozens or thousands or more. Eachtrainer is associated with at least one client and as many as dozens orhundreds of clients. Each client is typically associated with one or asmall number of trainers.

A partner is any kind of enterprise, for example, health care providers,and underwriters or a gym or a weight clinic, that provides, one or morebody composition management services directly to one or more clients (orindirectly to clients through one or more trainers). Each partner can beassociated with one or more trainers and with one or more clients or anycombination of them. Each trainer and each client can be associated withone or more partners. We sometimes refer to partners and trainers asproviders. In some cases an individual trainer can operate as a partner.

The system shown in FIG. 1 can be replicated by one or more othersimilar systems and the systems can be interconnected or independentlyoperated. Different systems can be operated in different geographicareas or by different partners or groups of partners, or by groups oftrainers, or even by groups of clients. Different systems can maintainindependent databases or can cooperate in the maintenance of jointdatabases.

Some of the database information about clients is personal, for example,their names and other identifiers, and other database information(including metrics and calculated values associated with bodycomposition and goals) is treated as anonymous, such as the height,weight, lean body mass, fat body mass, BMI, BMR, percentage of body fat,and others described later, that is, it is not tagged with any personalidentifiers. The effective use of some of the metrics and calculatedvalues in the database depends on statistical information accumulatedand analyzed across a larger population, for example, data thatassociates percentage of body fat with health conditions. The data basedon statistical information can be developed internally by the system,can be shared among systems, or can be received from an outside source60. Conversely, anonymous data in the database that is useful as part oflarger bodies of data about broader populations can also be shared amongdatabases and provided to an external user of such data 60. By suchsharing of anonymous data the effectiveness of the body compositionmanagement programs conducted using the system can be improved.

In some implementations, a system uses a single central web serverassociated with an application and a central database to provideservices for body composition management through the World Wide Web tocomputers and portable and handheld devices that are controlled by avariety of partners, a variety of trainers, and a variety of clients,who can have a range of relationships with one another.

In general, the system described here enables, among other things, (1)goals to be established, maintained, and adjusted over time for eachclient for raw and calculated metrics associated with body composition,good health, strength, and stamina, (2) a succession of measurements ofthe client over time with respect to the raw metrics to be acquired,stored, maintained, and accessed as needed by the client, her trainers,and her partners (with appropriate controls to protect privacy), (3)other metrics to be calculated, stored, maintained, and accessed fromthe raw metrics, (4) performance of the client against the goals to becalculated, displayed, stored, maintained, and accessed as needed, and(5) information to be accessed, displayed, understood, and usedinteractively through a simple, convenient user interface.

The system can make use of conventional metrics, including BMI, BMR,body fat percentage, weight, height, and others. In addition, the systemuses special metrics that are effective in managing body composition forgood health, strength, and stamina.

For this purpose, the system represents the relationship between actualbody masses (LBM and FBM) and desirable body masses in two ratios: aminimum lean mass ratio (MLMR) and a maximum fat mass ratio (MFMR). Theminimum lean mass ratio is the ratio of the actual lean mass of a personto a desirable minimum healthy lean mass (MLM) for the person. Themaximum fat mass ratio is the ratio of the actual fat mass to adesirable maximum fat mass (MFM) for a person. Positive values of MLMRindicate more than the minimal needed lean body mass and are consideredgood. Negative values of MLMR are considered bad. Positive values ofMFMR are considered bad (because the person has more than the desirablemaximum amount of fat) and negative values are considered good, exceptthat a very low value of MFMR may indicate a potential health risk.

We define a desirable body composition factor (BCF) that mathematicallydefines, based upon an analysis of statistical data across a population,the MFM and MLM for a person of a specific gender and height. Based onan example population that was analyzed for this purpose, the formulafor MLM and MFM for male and female subjects as a function of height is:

For males:MFM (pounds)=round(((height in meters/5.1423822805848300)*height ininches),0)MLM (pounds)=round(((height in meters/0.9795013867780630)*height ininches),0)in which 0 is the argument to the “round” function and indicates thatthe rounding is to zero places, that is, an even number of pounds.

For females:MFM (pounds)=round(((height in meters/3.29112465957429)*height ininches),0)MLM (pounds)=round(((height in meters/1.09704155319143)*height ininches),0)

For a person whose lean mass and fat mass match the desirable MFM andMLM values, the ratios MLMR and MFMR are both unity.

The BCF formulas may be updated and refined as more data from thegeneral population becomes available and can be analyzed statistically.For this purpose anonymous data in the databases may be shared andanalyzed.

The database can be in the form of a relational database that includes anumber of tables. Some implementations of the database can include thefollowing tables for that purpose. Other implementations could havedatabases and tables arranged in a wide range of ways, and can includemore or less information than the examples described here.

A table called “control” organizes system configuration parametersincluding, for example, as shown in FIG. 2, the version, the dateupdated, notes, a copyright notice, and current MFM and MLM values formales and females, which have been derived by statistical analysis.

A table called “people” contains one record for each person (e.g.,client) who is enrolled, for example, as shown in FIG. 3. The tablecontains specific identifying and demographic data related to theindividual that generally does not vary. The record also containscertain fixed measurements of the person that relate to body composition(or values calculated from the measurements), such as an initial bodyweight and a final fat mass. A key id_usr points to other tables thatcontain variable data about the person, such as regular informationaccumulated during body checks, activity and nutrition logs, and a dailyjournal. Also recorded in the “people” table is a logical indicationthat the terms of use (recorded in the “control” table) have beenaccepted and the date when the terms were accepted. Acceptance of theterms is required for enrollment. If the required terms changere-acceptance can be mandated.

The table “partners”, for example, as shown in FIG. 4, contains onerecord for each partner of the system. Records in the partners table canbe nested to document corporate relationships among partners. A partnerrecord contains pointers to graphical items used in the “private label”interface of the web pages that will be served to trainers and clientswho are users of that partner's services. This allows a common sharedinterface to be customized to reflect the brand of the partner, forexample, “Bill's Gym”. The partner record also contains data for thebase font, font color, font size, and background and foreground colors.The record is indexed using a unique system generated key value(partnerkey), which connects the record to the client record that isselected either during an individual's login or from a customized listof people provided to an authorized partner.

A table called “skins” is associated with the partners table and isused, for example, to maintain information necessary to establish thegraphic elements of the user interface. Recording interface elements inthe “skins” table allows multiple interface styles or “skins” to bedeveloped for each partner. These skins can be displayedprogrammatically for example, based upon time of year, client, trainer,or partner preference, or other factors.

A table called “bodycomp” (see FIG. 5) contains one record for each bodycheck of a person, including all raw numeric metrics collected duringthe body check. In some implementations, values that are computed fromthese metrics and other data on-the-fly by the application at the timeof display are presented through the user interface. This allows new oradjusted mathematical algorithms to be applied easily to the data as thealgorithms are developed. In other implementations, some or all of thecomputed values can be stored in the database and recalculated from timeto time. Each bodycomp record contains enough data to describeaccurately the physical state of the person at the time of collection.Compelling and statistically significant data may be obtained byanalysis of the anonymous data contained in these and other similarrecords.

Comparisons and analyses of the data may be made based upon any of themetrics recorded or calculated. Trend data may be developed over time.The data contained in each bodycomp record allows on-line calculationand reporting of statistical information relevant to an individual. Forexample, a 46 year-old man could ask for and view a scatter plot graphof his MLMR (in a unique color) compared to the MLMRs of all 46 year-oldmen recorded in the system or in a broad group of similar systems. In atext-based report, the value can be reported as a variation from themean, standard deviation, or other statistical measure. The system maybe enhanced by correlating current client body composition values withpotential health risks. For example, morbidly obese persons are at anincreased risk for heart disease and diabetes.

The system can accept body fat percentage values (BFP) from a variety ofsources, for example, by calculation from skinfold and circumferencemeasurements, from bio-electric-impedance (BEI), hydrostatic weighing,X-Ray and CAT scan analysis. Skinfold measurement is the most accurateof the easily applied techniques.

For each client, one or more goal sessions can be defined and tracked. Agoal session, for example, includes a starting date and an ending dateand goal values for one or more raw or calculated metrics that are to bereached at the ending date. A table called “goals” (FIG. 6) contains onerecord for each goal set (e.g., a body composition management program)established by or for a client. A client can have one or more than onegoal session, for example, a succession of goal sessions one after theother, or alternative goal sessions that overlap in time.

For example, as shown in FIG. 6, a goal session contains start and enddates, starting body fat percentage (BFP) and ending fat body mass andlean body mass values. Using relationships with other tables, one ormany body checks recorded at the beginning of and during the period of agoal session may be selected and displayed. The delta values between thestarting and ending (goal) fat body masses and lean body masses allowexpectation slopes (sometimes called glide slopes) to be developed andtracked during the course of the goal session. The values recorded inbody checks during the course of the session, when plotted against theexpectation slopes, provide feedback about the person's progress towardthe goals. The ending date and goals may be adjusted as needed.Nutrition and exercise components of the goal may be adjusted to matchthe person's actual performance and therefore better match theexpectation slopes to the person's capability. A wide variety of otherraw and calculated metrics can form the bases of the goal sessions, theexpectation slopes, and the body checks. In some implementations, othertables can also be maintained for reference purposes, among others. Forexample, an “activity” table (not shown) captures descriptions of humanactivities and the equivalent metabolic values. A “daily log” (FIG. 7)includes records each of which captures an instance of informationentered by a person concerning daily values such as weight, periods ofexercise, or a photograph. Each record of a “foods” table (not shown)associates food with details about its nutritional content and value.

A table called “charts” contains one record for each chart typedisplayed by the system. In concept, the table divides the chart intothree standard code blocks: header; body; and footer. These blockscontain the program code required to generate custom graphic objectsbased upon numeric data contained in other tables or produced byprogrammatic computation. The fourth element of the program code isgender specific and is recorded in the appropriately named gendermaleand genderfemale columns of the table. Data in the table are referencedby chartname and relationships are maintained with the system managedprimary index (chartkey).

In other implementations a wide variety of other raw and derived dataand the results of analyses of data also can be stored and madeavailable.

Examples of how the web-based user interface could be implemented for apartner that is serving trainers and clients are illustrated by the webpages shown in the figures and described as follows. A wide variety ofother interfaces would be possible, including interfaces suitable forsmall hand held or portable devices. A wide variety of types ofinformation and functionalities can be provided in the interface. FIGS.8 through 23 are provided as line drawing versions of full color orgray-scale images of screen shots to comply with patent office rules.The line drawing versions do not illustrate all of the color, shading,layout and other graphical aspects of the screen shots. Copies ofversions of the full color or gray-scale images from which the linedrawings were prepared are being submitted as an Appendix to thisapplication and are incorporated here by reference in their entirety.The applicant reserves the right to import any or all features shown inthe Appendix figures into the formal figures in this application,including the color features.

As shown in FIG. 8, an initial screen seen by a user (generally, when werefer to user we mean a person who is interacting with the userinterface, which could be a client, a representative of a partner, or atrainer, depending on the context) bears graphical elements defined inthe database for the partner on behalf of which the user interface isbeing served. The graphical elements include a logo, colors, pagebackground, font sizes and colors, and a greeting. The initial pageincludes two simple buttons. One button is invoked to join the systemthat is offered by the partner represented by the current instance ofthe user interface. The other button is used by a registered party (atrainer or a client) to login.

FIG. 9 shows the join screen that permits a new client to create aprofile by providing items of identification and contact information,set a password, and enter basic physical information. Clicking thebutton labeled Create Account causes a new record to be created in thepeople table of the database.

FIG. 10 is a similar screen that enables a trainer to create an accountfor a new client of the trainer. When the Create Client button isclicked, a new record is created in the people table of the database.

FIG. 11 shows an example of a typical login page, which requires theuser name (typically the person's email address) and the user'spassword.

If the user who logs in is a trainer or an administrator orrepresentative of a partner, the screen shown in FIG. 12 appears. In thecenter, a scrollable list of clients contains the names of people whohave joined and are therefore in the database and who are associatedwith that partner or that trainer (and other clients will not be shown).The trainer (we sometimes use the word trainer as including anadministrator or a partner) can then select a client whose informationis to be viewed. A navigation bar on the left of the screen has fivebuttons that enable the user to return to the home screen, entermeasurements and other data associated with a body check, viewinformation about the client, participate in a forum, or logout.

The screen for entering the date and results of body check measurementsis shown in FIG. 13 for a woman and in FIG. 14 for a man. When the Savebutton is clicked, the entered information is stored in the bodycomptable of the database.

If the user who has logged in is a trainer and has selected a client andclicked the client button (or if the user herself has logged in) thenthe screen shown in FIG. 15 will appear. The screen includes aphotograph of the client from the database, if one is available, and theclient's name. The client button on the left navigation bar has spawnedsub-buttons that enable the user to select to see a history of theclient's participation in the body composition management program, thegoals set by the client, or the radar display of the client's progress.

FIG. 16 shows a screen containing a history report that is invoked whenthe history sub-button of FIG. 16 is clicked. The information in thetable of FIG. 5 is drawn from the body check database records for theclient. The table provides information and access to other screens thatrelate to body checks for this client.

Each line of the table contains data from a record of the body checktable, including the date, measurements taken on that date, andcalculated values. Links on the right end of each row permit the user tonavigate to notes and photographs associated with the body check. A linkon the left end of each row leads to the full related body check report.The links along the top of the table are each associated with a chartover time of the indicated metric. Groups of charts can be invoked usingthe links along the bottom of the table. The links at the lower left ofthe chart enable the user to print the history report, create a new bodycheck record or edit an existing one.

When the goals sub-button on FIG. 15 is invoked, the screen shown inFIG. 17 is displayed. The client's goals of a goal session, plans formeeting those goals, and an illustration of how performing according tothe plan will affect progress toward the goals are provided in FIG. 17.

The goals page shown in FIG. 17 is a core instant feedback mechanism ofthe system. Upon completion of an initial body check, the goal trackingsystem extracts current body composition information and uses this dataas a starting point of the current goal program. The BCF values for theclient's actual MLM and MFM are computed when the application isinitialized. The values are computed using the core formulas recitedearlier based on the client's gender and height. These values are usedto populate roll-over icons which provide guidance for the goal settingprocess. Initially the goal tracking system presents the current leanand fat weights and computes macro nutrition values derived from thebase metabolic rate of the client.

The interface allows the client or the trainer to increase or decreasethe goals for fat body mass and lean body mass to establish new fat andlean weights. The end date when the goals are expected to beaccomplished can be selected from a graphical control. Upon selection,the system calculates the number of days in the goal session from thestart date and the end date. Numeric values may be adjusted for macronutritional elements (protein, carbohydrates, and fat). As these valuesare updated, the caloric values are computed and the impact is computedagainst the BMR determined from the current BodyCheck record. The impactof cardiovascular exercise is added to the plan by adjusting the numberof days on which cardio exercise is performed, and the number ofcalories expended per day of cardio vascular exercise.

The system can accurately factor in the caloric impact of otheractivities (yoga, palates, rollerblading, for example). This capabilityis based upon the BMR multiplied by the metabolic equivalency (met)value contained in the activity table. Thus, if a person has a BMR of2,400 calories per day (100 calories per hour) and engages in vigorousrope jumping (12 met) for 1 hour, she will have expended 1200 (12×100)calories. This accurate caloric calculation is an example ofcustomization to the individual characteristics of the client. In asimilar manner, the impact of resistance training is incorporated intothe plan as values representing the number of days in which the clientengages in resistance training and the number of calories expended perday. Each modification to fat mass or lean mass; dietary intake;cardiovascular expenditure; or exercise expenditure is immediatelyreflected in the cumulative impact section of the display. This allowsthe client or trainer to immediately understand the impact of any changemade in the goal program. When changes are complete, the settings arerecorded for future analysis. The system will not allow a client ortrainer to set a goal which is not realistically attainable.Additionally the system alerts when goal values may have negative healthimpact.

The table in the upper left corner shows the client's body compositiongoals and current metrics, including the client's current fat mass, leanmass, and total mass in the first column, the goal for those metrics inthe second column (these can be adjusted using the adjustment buttons),and the change (in the third column as a value and in the fourth columnas a percentage) from the current values to the goals that are impliedby the first two columns. The bottom row shows the calories thatcorrespond to the current base metabolic rate (BMR) which is inferred bycomputation from the current fat body mass and lean body mass values,and from the goal mass values. Base metabolic rate is a gender neutralvalue that may be computed as round(((1.3*(leanmass (inpounds)/2.2))*24),0), which yields the approximate number of calorieswhich are required by the client to exist in a resting state withoutgaining or losing weight. Calories necessary for walking about, fooddigestion, and exercise are in addition to this amount. The basic dietrecommendations are obtained by the following formulas, which representthe minimum nutrition values required to support a client's individuallean body mass. For males, Protein calories=LBM*1.1; Carbohydratecalories=LBM*1.0; Fat calories=LBM*0.3. For females, Proteincalories=LBM*1.0; Carbohydrate calories=LBM*0.8; Fat calories=LBM*0.3.

The table in the lower left illustrates a planned diet mix for caloricintake combining protein, carbohydrate, and fat. The first column setsforth the amount of each in grams and permits adjustment of the goals.The second column shows the conversion of grams to calories, and thethird column shows the number of grams per pound of the client's weight.The total number of calories is compared to the calculated number ofcalories that correspond to the BMR for the client, and the calculatedvariance is shown in the bottom row. A negative variance represents ashortfall of calories compared to BMR which would translate into thebody using stored calories to make up the deficit (and conversely).

The table in the middle of the bottom of FIG. 17 captures the client'scardio plan, that is the plan for vigorous cardio-vascular exercise thattends to burn calories. The number of days per week in which cardioexercise would be done (five in the example shown) is adjustable. Theexpenditure of calories for each of the exercise days would be 300 (anadjustable number) in this example, yielding a calculated totalexpenditure of 1,500 calories per week.

In the lower right is a strength training plan that sets an adjustablegoal for the number of lifting days per week and a number of caloriesexpended in each day, with the calculated total appearing in the bottomrow. The strength training plan relates to exercise intended to buildlean body mass.

In the upper right, the system displays to the user information thatimplies how much progress the client is expected to make toward thegoals per week during the goal session. The displayed values include themeasured percentage of body fat, the calculated BMR in calories, and thecalculated calories stored as fat. The calculated total caloric deficitrepresents the number of calories of fat body mass that must be lost inorder to reach the goal amount of fat body mass. The next three linesshow the deficits that would be attributable to reducing food calories,to exercise (including cardio and weight), and to the total of those twovalues. The deficit values are recalculated in real time as goal valuesare changed by the user in the various tables. In the example, the totaldeficit is 4,244 calories which corresponds to a calculated weightchange per week of 1.21 pounds.

This weight reduction is to be achieved not only by reducing thecalories eaten, but also by cardio exercise and strength training. Theclient's goals in the upper left table include no loss of lean bodymass. The strength training plan is designed to assure the maintenanceof lean body mass as the total weight of the client is reduced. This isachieved by calculating the protein needed to meet the requirements ofthe lean mass using a grams per pound calculation. The result isadjusted using judgment based on the mid-point readings taken during thecourse of the goal session. These readings allow the client's currentbody composition to be compared with the body composition expected atany mid-point date in the goal session. With these readings, quickadjustments may be made to diet and exercise plans. The client may alsobe taught that as fat is lost from the body some percentage of it willbe lost from inter-muscle tissue. This will increase the overall qualityof the muscle, but may result in a minimal loss of lean mass. It is alsopossible to calculate, report, and manage the quality of muscle (leanbody mass). Measurements may be done using electromyography (EMG), whichreports the electrical activity of a muscle under contraction. Thevalues rise with the strength (quality) of the contraction. When aclient is properly instrumented (electrical leads attached to the musclegroup being studied), values may be recorded for specific muscle groupsand exercises. Over time, the values recorded while the muscle is undercontraction will increase. The ratio of change between earlier and laterreadings may be used to compute a lean mass ratio LMR quality factor.For example an initial reading obtained while the pectoral muscle isunder contraction may be 200.38 microvolts. A later reading might be210.34 microvolts. This results in a ratio of 1.0497. The ratios may begraphed to show variation over time. Various methods exist for themeasurement of muscle contraction including, for example, tension, andvelocity. Studies may also be performed to measure the quality andquantity of fast and slow twitch muscle fibers and their respectivecontractions; these values can be used in the measurement of strengthand stamina of the client's lean body mass. Other methods fordetermining muscle quality may be included.

Returning to the table in the upper left of FIG. 17, at the left end ofeach row is a dot the color of which provides more information inresponse to a rollover of the mouse cursor, for example, as shown inFIG. 18. A dot also can be colored (red-bad, yellow-caution, green-good)to provide visual feedback regarding the values being set. Other graphicelements, such as a dumbbell, a light bulb, and a starburst, could alsobe used.

The performance dial in the upper center of FIG. 17 uses a circularanalog dial and dial pointers to indicate progress against goal. In theexample shown, a goal for percentage body fat is indicated by a greenneedle. An actual current percentage of body fat is shown by a redneedle. Other needles could be used for other raw and calculatedmetrics.

The goal numbers set by the user can be saved and recalled using thesave goal and recall goal buttons.

When a user invokes the Radar sub-button on the navigation bar of FIG.15, he may be shown a radar plot, for example, the plot shown in FIG.19. The y-axis of the plot represents the MLMR and the x-axis the MFMR.The center point of the plot represents a locus in which both ratioshave the value of 1, that is, the ratios of the minimal lean body massand maximum fat body mass to the goal values are both 1. The scale ofvalues along each axis can expand or contract depending on the locationof the values to be plotted. For example, for a fat person, the scalefor MFMR could have a right end that is higher than 4. The center pointrepresents a desirable state for the client's fat mass ratio and leanmass ratio. The optimum state of those values for a given client mayvary from the center point depending on his or her personal goals orrequirements. For example, the optimum fat mass ratio may besubstantially below 1.0.

Dots on the plot can indicate the two ratios at different times.Although not shown in color on the figure, an example is shown in FIG.19. The initial value may be shown in red, the most recent value ingold, and an intermediate value in blue. The color and size may also beadjusted to emphasize other elements, such as dangerously low body fat.Plotted points that are closer to the upper left of the radar plotindicate excess lean body mass (compared to the minimum desirable) andreduced fat body mass (compared to the maximum desirable), which areboth positive indicators. Conversely, points that are closer to thelower right indicate unfavorable values. The radar plot uses twodifferent graphical features to inform the viewer. Again, although thefigure reproduced here does not show color, background colors of yellowand orange may be used to imply increased health risk and of red toimply definite health risk. A background color of green may implyfavorable conditions. In addition, pie-shaped segments of the plot aredefined by rays that project from the lower left corner. Points that liewithin a given segment represent roughly similar body compositionconditions. Thus, it would typically be useful to engage in a trainingprogram that results in moving generally from the lower right toward theupper left across segment boundaries rather than to move from one pointto another point within a given segment.

The table shown below the plot contains key values from the body checkhistory. Each row represents a body check.

When the body check button on FIG. 12 is clicked, the screen shown inFIG. 20 may be presented to the user. This screen presents the main dataentry form for body check data. The entered data is used to populate arecord of the database.

When the user invokes one of the columns in the body check history table(which is shown larger in FIG. 21), a chart is displayed. An example isshown in FIG. 22, which tracks abdominal skin fold values over timebased on the dates when the body checks were made. The charts of thekind shown in FIG. 22 are generated using FusionCharts (available fromInfoSoft Global (P) Ltd., located in India). The links that areavailable in the table of FIG. 16 allow immediate drill down to chartslike the one shown in FIG. 22 and thus provide immediate quantifiableand personal feedback to the client about his or her physical state,history, and history of measured performance.

For a given body check, the metrics accumulated and values calculatedfrom the metrics can be shown to a user in graphical form, for example,as shown in FIGS. 23A, 23B, and 23C.

The database associates historical and current data about an individualclient with the client's name or other identifier, in order to enablethe trainer, partner, or client to use the data for personal andindividual purposes. In addition, the information in the database may beaccumulated and reported in a manner that disassociates the current andhistorical data from the personal identification information. Thedatabase is structured to permit simple queries of a kind that gather oraccumulate individual values and statistical data that is anonymous. Forexample, a query could obtain the mean body fat percentage for malesbetween the ages of 40 and 50. In a central server a database can bemaintained that is anonymous or non-anonymous. Data can be keptanonymous by permitting identifying information to be accessed only whena correct combination of user name and password yield a unique personkey (id_usr). Only with this key can identifying information be unlockedfrom the database. However, statistical queries can be run against thebodycomp table which contains no user identifiable information apartfrom a link back to the people table. When system maintained queries,are used identifiable information is not revealed. Passwords arerequired for administrator access and these are controlled and changedon a regular basis.

In some implementations, the database and the calculation engine may bearranged, for example, so that only raw measured values or user entereddata are stored persistently while calculated values are not stored butare calculated only as needed. In this way, if measured values orentered data needs to be corrected, the calculated values do not have tobe recalculated until they are needed. In addition, the database canstore a broader range of raw values and entered data that is used at agiven time for calculations. By storing the measured values in raw form,when refinements are made later to the formulas for calculating derivedvalues from possibly a different or more comprehensive set of rawvalues, the values are easily available in the database. Among otherthings, this will permit the derived values to be customized based ongender, ethnicity, age, body type (ectomorph, mesomorph, endomorph), orextreme value of fat mass or lean mass.

The use of roll-over dots throughout the user interface provides simpleand quick information to a user concerning good (green), caution(yellow), and bad (red) values to be considered. When the mouse cursoris rolled over a dot additional detailed information about the conditionbecomes available.

As shown in FIGS. 24, 25, and 26, based on stored actual and goal values(for starting and ending fat weight, lean weight, and composite weight,and the client's base metabolic rate (BMR) derived from body checks),the amount of expected fat loss per day and progressions of lean weightand composite weight that will be produced by a planned program can becalculated. This allows a straight-line graph (which we sometimes call aglide slope) from an upper left starting point to the lower right targetfinish point, of expected progress, to be produced and used as afoundation for a multi-series graph that plots actual progress overexpected progress. On each date when a body check is performed, theresulting point is charted on FIG. 24 together with a path segment. Thisprovides immediate feedback to the client regarding her progress towardpersonal goals and immediate confirmation that progress is on track orthat a goal is in jeopardy. Minor variations from the glide slope willresult in messages recommending modification to nutrition,cardiovascular and resistance training plans. Major variations willtrigger a recommendation to revisit the goal setting tool. The goalsetting tool may be used to adjust nutrition or exercise values to bringgoal and reality into synchronization. More frequent body checks provideopportunity for feedback and confirmation of progress. This allows theclient and the trainer to make small modifications to keep progress ontrack and helps maintain motivation.

In the example shown in FIG. 24, the vertical scale is of weight, theglide slope represents a linear path of the weight, and the pathsegments from point to point relate to weight. However, other glideslopes (such as those in FIGS. 25, 26, and 27) can be used either aloneor in a suite to show the progression of lean mass ratio, fat massratio, and total mass, or other metrics along the vertical axis. Allsuch values or other combinations of values could be illustrated on asingle graph. In such an example, a single straight glide slope couldrepresent the anticipated trajectory of all of weight, lean mass ratio,fat mass ratio, and other metrics. Then actual progress on each of themetrics could be illustrated by a separate path. Or different glideslope lines could be shown together with actual trajectories. Ordifferent graphs could be used and displayed independently asillustrated in the figures. In some implementations, the glide slopecould be other than a straight line and could represent another desiredor feasible trajectory. For example, the trajectory could represent morerapid changes in the value at the beginning and less rapid changes asthe target final value is approached.

As shown in FIG. 28, another graphical tool that can be displayed to auser to help guide body composition management relates to a factor thatwe call body mass tension (BMT). One use of BMT is to provide moreuseful information than is encompassed in a conventional use of BMI.Conventional BMI, which is based only on weight and height, does nottrack or provide any indication of the contributions of lean body mass(or lean mass ratio) or fat body mass (or fat mass ratio) to theresulting BMI value. For example, a BMI value can be low and seeminglyrepresent a healthy individual, even though the individual actually hasinsufficient lean mass and excess fat mass. Conversely, an individualwho has a high conventional BMI may be quite healthy when viewed inlight of the person's relatively high lean body mass.

BMT exposes these inaccuracies of conventional BMI. In FIG. 28, the xaxis represents values of BMI. The vertical line 110 at 21.75 indicatesthat, under a classic view of BMI, a normal BMI 116 for the client is21.75. Thus, if the client's BMI were to reach 21.75 after a goalsession were completed, under this classic view, the client would be ina good state. We refer to 21.75 as the legacy BMI value 116.

The portion of FIG. 28 above the x-axis is a conceptual graphical devicethat illustrates how the acceptable BMI value for a client can beadjusted using a BMT factor 117 based on the actual or plannedcomposition of the client's body in terms of fat mass ratio and lean(e.g., muscle) mass ratio. The conceptual graphical device comprises thevertical line 110 and two bows 112 and 111 that lie to the left andright of the vertical line. The shapes of the two bows are somewhatarbitrary and are intended to suggest tension that is placed on thevertical line to pull it to the left or right, depending on the fat massratio and the lean mass ratio. The fat mass ratio is represented by thelength of a bar 114 that has a base lying on the vertical line and atension-applying end at the left. The lean mass ratio is represented bythe length of an opposite bar 115 that has its base on the vertical lineand a tension-applying end to the right. The lean mass bar conceptuallycan pull the ideal BMI value to the right and the fat mass barconceptually can pull the ideal BMI value to the left. The compositeimpact of the two bars on BMI is represented by the product of the leanmass ratio and the fat mass ratio. Multiplying the result of thatproduct by the conventional BMI yields the BMT-adjusted BMI value.

If both ratios were 1.0, for example, their product would be 1.0 andapplying that factor to the BMI would cause no change in the BMI value.

In a traditional BMI scale, less than 18.5 is considered underweight,between 18.5 and 25 is considered normal, and 21.75 is the mid-point ofthe normal range and the range extends +/−3.5 points on either side ofthe mid-point for the normal range. 25 to 30 is considered overweight,30 to 35 as obese, 35 to 40 as very obese, and more than 40 as very(morbidly) obese.

The adjusted BMI value that results from applying the BMT factor can beviewed as shifting the entire BMI scale in accordance with bodycomposition data for an individual. In the example of FIG. 28, all BMInumbers would be shifted to the right by 2.849 points, which isdetermined by the formula: BMI shift=((CBMI*(LMR*FMR))−CBMI) (in whichCBMI refers to center BMI which is the center value in the normal rangein the conventional BMI scale). In the example of FIG. 28, this formulayields ((21.75*(1.3*0.87))−21.75)=2.849.

BMT also can be viewed in a different way, as a factor which issubtracted from the measured actual BMI of a client to correct thevalue, in this case the corrected value being the calculated BMI of 26.7(based on measured height and weight) minus the adjustment of2.849=23.851 (based on body mass composition). This resulting value isin the normal range of the traditional BMI scale. Thus we have correctedthe traditional BMI rating of 26.7 (considered overweight) to 23.851(considered normal).

The client represented in FIG. 28 had an actual BMI of 26.7 (based onweight and height), and might have been told, under a conventional BMIanalysis, that she had an increased health risk and an overweightcondition relative to a desirable BMI of 21.75. However, the client'sLMR was 1.3 and FMR was 0.87 suggesting that a conventional BMI targetwas not appropriate to her situation. Multiplying the LMR (1.3) by theFMR (0.87) yielded a BMT correction factor of 1.31. When applied to thetraditional BMI value of 21.75, the target BMT-corrected BMI valueshifted from 21.75 to 24.6, indicating that the client's actual BMI(when adjusted by the factor of 2.849 to 23.851), was acceptable and inthe normal range. Illustrating the effect of BMT on BMI helps trainers,health care practitioners, and insurance companies recognize theimportance of the relationship between body composition and overallhealth. A wide variety of other graphical elements and devices could beused to illustrate the impact of lean mass and fat mass on theinterpretation of conventional BMI values.

More generally, it is possible to generate a target value for a clientbased on the person's weight, height, fat body mass, lean body mass, andcorresponding physical and demographic characteristics of a populationof individuals, which more accurately reflects the desired body massindex taking account of the client's body composition than is the casewith the conventional BMI. The generated value can be expressed in termsof an adjustment of a conventional BMI value or in any other usefulmetric.

Other implementations are within the scope of the following claims.

1. A method comprising: generating a target value associated with atargeted fat mass and lean mass body composition of a person to beachieved by a future date, enabling display electronically of a slopethat begins at a starting point associated with a starting date and endsat an ending point associated with the future date, the starting pointrepresenting a starting value associated with a fat mass and lean massbody composition of the person that is determined based on measurementson the starting date, the slope being based on the starting value andthe target value, and enabling display electronically of a trajectorythat traverses intermediate points between the starting date and thefuture date, the intermediate points having values that are based onmeasurements of the fat mass and lean mass body composition of theperson on dates between the starting date and the future date.
 2. Themethod of claim 1 in which the target value is associated with weight.3. The method of claim 1 in which the target value is associated with acomponent of body mass.
 4. The method of claim 3 in which the componentof body mass comprises fat mass or lean mass.
 5. The method of claim 1in which the target value is associated with a ratio for a component ofbody mass.
 6. The method of claim 5 in which the ratio comprises fatmass ratio or lean mass ratio.
 7. The method of claim 1 in which theslope comprises a straight line.
 8. The method of claim 1 in which theslope and the trajectory are displayed at the same time.
 9. The methodof claim 1 in which the slope and the trajectory are associated with agoal session for the person.
 10. A method comprising: generating atarget value associated with a targeted fat mass and lean mass bodycomposition of a person to be achieved by a future date, enablingdisplay electronically of a proposed trajectory that extends from astarting value associated with a fat mass and lean mass body compositionof the person on a starting date to the target value at the future date,enabling display electronically of a measured trajectory that extendsfrom the starting value and traverses intermediate measured valuesassociated with the fat mass and lean mass body composition of theperson on dates after the starting date, and enabling at least twodifferent independent providers of body composition management servicesto have online access through respective graphical user interfaces todisplay the proposed trajectory and measured trajectory.
 11. A methodcomprising: generating a target value associated with a targeted fatmass and lean mass body composition of a person to be achieved by afuture date, displaying electronically a slope that begins at a startingpoint associated with a starting date and ends at an ending pointassociated with the future date, the starting point representing astarting value associated with a fat mass and lean mass body compositionof the person that is determined based on measurements on the startingdate, the slope being based on the starting value and the target value,displaying electronically a trajectory that traverses intermediatepoints between the starting date and the future date, the intermediatepoints having values that are based on measurements of the fat mass andlean mass body composition of the person on dates between the startingdate and the future date, and enabling at least two differentindependent providers of body composition management services to haveonline access through respective graphical user interfaces to thedisplayed slope and trajectory, at least some of the graphical userinterfaces for different independent providers being different.
 12. Themethod of claim 10 or 11 in which the providers include trainers andentities that employ trainers.
 13. The method of claim 10 or 11 in whichthe graphical user interfaces include common elements and private labelelements.
 14. The method of claim 11 in which the independent providersaccess the displayed slope and trajectory through the Internet.
 15. Themethod of claim 10 in which the independent providers access to displaythe proposed trajectory and the measured trajectory through theInternet.
 16. The method of claim 10 or 11 in which the providersinclude health professionals or health care providers.
 17. The method ofclaim 1 in which enabling display of the slope and the trajectorycomprises enabling display of through the Internet.
 18. The method ofclaim 1 or 11 in which the slope comprises a declining slope.
 19. Themethod of claim 10 in which the proposed trajectory comprises adeclining trajectory.
 20. The method of claim 1 further comprisingenabling display of additional slopes, each slope associated with oneparameter of a body composition of the person.
 21. The method of claim11 further comprising displaying additional slopes, each slopeassociated with one parameter of a body composition of the person. 22.The method of claim 10 further comprising enabling display of additionalproposed trajectories, each proposed trajectory associated with oneparameter of a body composition of the person.
 23. The method of claim20 or 21 in which at least some of the slopes have opposite directions.24. The method of claim 22 in which at least some of the proposedtrajectories have opposite directions.